10X Rock — Free Stock Research & Investment Education

A professional-grade stock research platform combining quantitative analysis, AI-powered signals, and a free academic-style investment education library — built for serious US market investors.

What is 10X Rock?

10X Rock is a free, browser-based stock research platform that brings hedge-fund-grade analytical tools to retail investors. The platform combines seventeen integrated research tools — from regime detection models and quantitative factor analysis to insider transaction monitoring and small-cap discovery scanners — with a growing library of long-form investment education articles.

Unlike most retail finance platforms that focus on either charts or news, 10X Rock is built around a core thesis: that the same statistical methods used by quantitative hedge funds (Hidden Markov regime detection, Ornstein-Uhlenbeck mean reversion, Kalman filter trend tracking, CAPM alpha/beta decomposition, the Kelly Criterion) are accessible to individual investors when presented in an understandable interface. Every model on the platform is grounded in peer-reviewed academic finance, with primary references cited in our educational articles.

Free Investment Education Library

Our blog publishes original long-form articles on quantitative investing, risk management, factor investing, and US market education. Each article is written to be both accessible to beginners and substantive enough to be useful to experienced investors. Topics covered include:

Post-Earnings Announcement Drift (PEAD): The 50-Year Anomaly — Why stocks continue drifting for 60 days after positive earnings surprises, citing Bernard & Thomas (1989) and Chordia & Shivakumar (2006), with practical filters covering surprise magnitude, guidance revisions, revenue quality, beat streaks, and sector momentum.
Long-Term Compounding: The Eighth Wonder of the World — Why decades of compounding dwarf any short-term trading strategy, with case studies of Visa, Mastercard, Eli Lilly, and Microsoft, plus the academic evidence from Jeremy Siegel's two centuries of US equity return data.
Bottom Fishing: When the Falling Knife Is Actually a Bargain — The contrarian investing framework grounded in De Bondt & Thaler (1985) and Lakonishok, Shleifer & Vishny (1994), with seven technical capitulation signals and the quality filters that separate buyable bottoms from value traps.
Insider Buying Signals — Why corporate executives beat the market, citing Lakonishok & Lee (2001) and Cohen, Malloy & Pomorski (2012). Cluster Buy mechanics and CEO/CFO information value.
Micro-Cap Investing: The Liquidity Blind Spot — The Fama-French Size Factor explained, the structural advantage retail investors have in segments where hedge funds cannot operate at scale, and quality filters to avoid the value trap.
Beta and Alpha Explained — A complete guide to CAPM, Jensen's Alpha, and Beta with concrete worked examples for SPY, NVDA, and a multi-stock portfolio.
The Sharpe Ratio Guide — Why two 20% returns are not equal, and how professional investors compare investments on a risk-adjusted basis. Covers the Sortino Ratio as well.
10 Backtesting Mistakes That Will Wreck Your Portfolio — Lookahead bias, survivorship bias, overfitting, transaction-cost neglect. The expensive errors every retail trader makes.
The Kelly Criterion for Position Sizing — The mathematical foundation for optimal bet sizing used by Edward Thorp and Warren Buffett. Why Half-Kelly is the professional standard.
Hidden Markov Models for Market Regime Detection — The tool quantitative hedge funds use to identify bull, bear, sideways, and volatile market states in real time.
Mean Reversion vs Trend Following — Two of the oldest competing philosophies in finance, when each works, and how the smartest funds combine them.
How to Read an Earnings Report: A Beginner's Guide — The five sections that matter, beat vs miss, why guidance trumps results, and reading the 10-Q like a pro.
Sector Rotation: The Macro Strategy Hedge Funds Actually Use — The 11 SPDR sectors, the four-phase business cycle, and practical rules for sector ETF trading.

The full library lives at tentimesrock.com/blog, with new articles published regularly on topics ranging from short squeeze mechanics to long-term compounding strategies.

Quantitative Tools for Retail Investors

The platform's seventeen research tools are organized into five tiers based on a typical research workflow:

Tier 1 — Daily Market Context

News Radar aggregates market-moving stories with AI-generated impact analysis. The Daily Signal scanner ranks the day's top twenty stocks using a composite of seven weighted technical indicators combined with Kelly position sizing. The Sector Heatmap visualizes 1-day through year-to-date returns across the eleven SPDR sector ETFs to identify which areas of the market are leading or lagging.

Tier 2 — Stock Discovery

The Value Radar combines fundamental ratios (P/E, P/B, PEG, EV/EBITDA) with technical mean-reversion indicators to surface undervalued stocks. The Bottom Scanner identifies oversold names using a composite of seven mean-reversion signals. Long-Term Champions screens for stocks that have delivered strong risk-adjusted compound returns over one-, three-, five-, and ten-year horizons.

Tier 3 — Deep Analysis

The Quant Engine provides ten-model analysis per individual ticker, including Hidden Markov regime detection, GARCH volatility forecasting, Ornstein-Uhlenbeck mean-reversion modeling, Kalman filter trend tracking, Fast Fourier Transform cycle detection, Geometric Brownian Motion Monte Carlo simulation, and Hurst exponent calculation. The Track Record page automatically logs every Daily Signal pick and tracks one-day, one-week, and one-month forward returns against the SPY benchmark — providing transparent, auditable performance data.

Tier 4 — Trade Execution Planning

The Earnings Calendar covers fifteen hundred plus US companies with outlook and historical beat-miss data. The Trade Sizer calculates ATR-based stop-loss levels, Kelly Criterion position sizes, and expected value before entry. The Trade Plans menu saves these plans and tracks them through their full lifecycle (planning, active, closed) with automatic R-multiple calculation. The Backtester validates trading rules against historical data with proper Buy-and-Hold comparisons.

Tier 5 — Advanced and Niche Tools

Alpha Lab treats a watchlist as a virtual portfolio and computes portfolio-level beta, Jensen's alpha, Information Ratio, Sharpe and Sortino ratios, and four-factor exposure analysis. The Insider Tracker monitors SEC Form 4 filings for cluster buy patterns. The Micro-Cap Scanner filters small-cap stocks for combined growth, momentum, and quality factors. The Squeeze Radar identifies short-squeeze setups using short interest, days-to-cover, and volume-spike analysis.

Our Methodology

Every quantitative model on the platform is implemented from established peer-reviewed academic finance literature. We reference primary sources including:

Sharpe (1964) and Lintner (1965) for CAPM and the foundations of alpha/beta decomposition
Banz (1981) and Fama-French (1992, 1993) for the Size Factor and Three-Factor Model
Lakonishok & Lee (2001) and Cohen, Malloy & Pomorski (2012) for insider trading signal value
Bollerslev (1986) for GARCH volatility modeling
Kelly (1956) for the optimal position sizing formula
Baum-Welch and Viterbi algorithms (Baum 1972) for Hidden Markov regime estimation

We do not invent new theories — we implement the established ones transparently, with full documentation in our educational articles. This commitment to academic rigor is one reason 10X Rock has been adopted by serious individual investors who want institutional-quality analysis without subscription fees.

What 10X Rock Is Not

To be unambiguous about our scope: 10X Rock is an information and analysis platform. It is not a brokerage and does not execute trades. We are not registered investment advisors and we do not provide personalized financial advice. The signals, screens, and analytical outputs the platform generates are statistical patterns from historical and current market data — they are inputs to a research process, not stock recommendations. Past statistical patterns do not guarantee future returns, and individual investment decisions must be based on each user's own thorough review, judgment, financial situation, and risk tolerance.

Important Disclaimer: This service provides investment information for educational purposes only and does not constitute regulated investment advisory or discretionary investment services. Individual buy and sell decisions must be made based on your own thorough review and judgment. Past performance, backtest results, and statistical patterns do not guarantee future returns. Consult a licensed financial professional when making investment decisions appropriate to your individual financial situation.

Get Started

The interactive platform loads automatically. Navigate to About for a deeper overview of our methodology, browse the Blog library for educational articles, or reach out via the Contact page with questions, bug reports, or feedback. All tools are free to use without registration or subscription.